Computational methods for understanding bacterial and archaeal genomes /:
Over 500 prokaryotic genomes have been sequenced to date, and thousands more have been planned for the next few years. While these genomic sequence data provide unprecedented opportunities for biologists to study the world of prokaryotes, they also raise extremely challenging issues such as how to d...
Gespeichert in:
| Weitere Verfasser: | , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
London : Hackensack, NJ :
Imperial College Press ; Distributed by World Scientific Publishing,
©2008.
|
| Schriftenreihe: | Series on advances in bioinformatics and computational biology ;
v. 7. |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Zusammenfassung: | Over 500 prokaryotic genomes have been sequenced to date, and thousands more have been planned for the next few years. While these genomic sequence data provide unprecedented opportunities for biologists to study the world of prokaryotes, they also raise extremely challenging issues such as how to decode the rich information encoded in these genomes. This comprehensive volume includes a collection of cohesively written chapters on prokaryotic genomes, their organization and evolution, the information they encode, and the computational approaches needed to derive such information. A comparative. |
| Beschreibung: | 1 online resource (xix, 473 pages) : illustrations (some color) |
| Bibliographie: | Includes bibliographical references (pages 397-466) and index. |
| ISBN: | 9781860949838 1860949835 |
| ISSN: | 1751-6404 ; |
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| 245 | 0 | 0 | |a Computational methods for understanding bacterial and archaeal genomes / |c editors, Ying Xu, J. Peter Gogarten. |
| 260 | |a London : |b Imperial College Press ; |a Hackensack, NJ : |b Distributed by World Scientific Publishing, |c ©2008. | ||
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| 490 | 1 | |a Series on advances in bioinformatics and computational biology, |x 1751-6404 ; |v v. 7 | |
| 504 | |a Includes bibliographical references (pages 397-466) and index. | ||
| 588 | 0 | |a Print version record. | |
| 505 | 0 | |a Preface; CONTENTS; List of Contributors; Acknowledgments; 1. General Characteristics of Prokaryotic Genomes Jan Mr ́azek and Anne O. Summers; 1. Introduction; 1.1. The Replicon Concept and Classification of Replicons; 1.2. Physical Organization of Replicons in the Cell; 2. Overall Properties of Prokaryotic Chromosomes; 2.1. Size and Gene Content; 2.2. Why Are Prokaryotic Chromosomes Small?; 2.3. G+C Content; 2.4. Oligonucleotide Composition and Genome Signature; 2.5. Amino Acid Composition and Adaptation to Growth at High Temperatures; 3. Heterogeneity of Prokaryotic Chromosomes. | |
| 505 | 8 | |a 3.1. Intrachromosomal Variance of Nucleotide and Oligonucleotide Composition3.2. Synonymous Codon Usage; 3.3. Identification of Genomic Islands and Lateral Gene Transfer Events; 3.4. G-C Skew; 4. Repeats in Prokaryotic Genomes; 4.1. Large Repeats and Duplications; 4.2. Transposons and Insertion Sequences; 4.3. Integrons; 4.4. Chimeric Mobile Elements: Conjugative Transposons, ICEs, Plasmid-Prophages, Transposon-Prophages, Genomic Islands, and Genetic Litter; 4.5. Retrons; 4.6. Short Dispersed Repeats; 4.7. Simple Sequence Repeats; 4.8. CRISPR Repeats; 5. Further Reading; Acknowledgments. | |
| 505 | 8 | |a 2. Genes in Prokaryotic Genomes and Their Computational Prediction Rajeev K. Azad1. Introduction; 2. Inhomogeneous Markov Models; 2.1. The GeneMark Program; 3. Interpolated Markov Models; 3.1. The Glimmer Program; 3.2. Using Deleted Interpolation in Gene Prediction; 4. Hidden Markov Models; 4.1. The Forward-Backward Algorithm; 4.2. The Viterbi Algorithm; 4.3. HMM Training; 4.4. The ECOPARSE Program; 4.5. The GeneHacker Program; 4.6. HMM Versions of the GeneMark Program; 5. Fourier Transform Methods; 5.1. The GeneScan Program; 5.2. The Lengthen-Shu.e Program; 6. Self-Organizing Maps. | |
| 505 | 8 | |a 6.1. The RescueNet Program7. Directed Acyclic Graphs; 7.1. The FrameD Program; 8. Linear Discriminant Function; 8.1. The ZCURVE Program; 9. Unsupervised Model Training: The Self-Learning Algorithms; 9.1. The GeneMark-Genesis Program; 9.2. The GeneMarkS Program; 9.3. The MED Program; 10. Using Similarity Search in Gene Prediction; 10.1. The ORPHEUS Program; 10.2. The CRITICA Program; 10.3. The BDGF Program; 10.4. The EasyGene Program; 10.5. The GISMO Program; 11. Gene Start Prediction; 12. Resolving Overlapping Genes; 13. Non-coding RNA Gene Prediction; 14. Assessing Gene Prediction Programs. | |
| 505 | 8 | |a 15. Discussion16. Further Reading; Acknowledgments; 3. Evolution of the Genetic Code: Computational Methods and Inferences Greg Fournier; 1. Introduction; 1.1. The Amino Acids; 1.2. Codon Designations; 1.3. Transfer RNA; 1.4. Aminoacyl-tRNA Synthetases; 2. Major Methods and Algorithms: Variations of the Genetic Code; 2.1. Non-canonical Codes; 2.2. Selenocysteine; 2.3. Pyrrolysine; 2.4. The Sep System; 2.5. Asparagine and Glutamine; 2.6. Evolutionary Considerations; 2.7. Nanoarchaeal tRNA; 3. Major Methods and Algorithms: Models of Genetic Code Evolution; 3.1. Overview. | |
| 520 | |a Over 500 prokaryotic genomes have been sequenced to date, and thousands more have been planned for the next few years. While these genomic sequence data provide unprecedented opportunities for biologists to study the world of prokaryotes, they also raise extremely challenging issues such as how to decode the rich information encoded in these genomes. This comprehensive volume includes a collection of cohesively written chapters on prokaryotic genomes, their organization and evolution, the information they encode, and the computational approaches needed to derive such information. A comparative. | ||
| 650 | 0 | |a Microbial genetics |x Data processing |v Textbooks. | |
| 650 | 0 | |a Bacterial genomes |x Data processing |v Textbooks. | |
| 650 | 0 | |a Prokaryotes |v Textbooks. | |
| 650 | 0 | |a Computational biology |v Textbooks. | |
| 650 | 0 | |a Bacterial genomes. |0 http://id.loc.gov/authorities/subjects/sh2003008346 | |
| 650 | 0 | |a Microbial genetics. |0 http://id.loc.gov/authorities/subjects/sh85084760 | |
| 650 | 2 | |a Genome, Bacterial | |
| 650 | 2 | |a Genome, Archaeal |0 https://id.nlm.nih.gov/mesh/D020745 | |
| 650 | 2 | |a Genetics, Microbial | |
| 650 | 2 | |a Computational Biology |x methods | |
| 650 | 6 | |a Génomes bactériens. | |
| 650 | 6 | |a Génétique microbienne. | |
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| contents | Preface; CONTENTS; List of Contributors; Acknowledgments; 1. General Characteristics of Prokaryotic Genomes Jan Mr ́azek and Anne O. Summers; 1. Introduction; 1.1. The Replicon Concept and Classification of Replicons; 1.2. Physical Organization of Replicons in the Cell; 2. Overall Properties of Prokaryotic Chromosomes; 2.1. Size and Gene Content; 2.2. Why Are Prokaryotic Chromosomes Small?; 2.3. G+C Content; 2.4. Oligonucleotide Composition and Genome Signature; 2.5. Amino Acid Composition and Adaptation to Growth at High Temperatures; 3. Heterogeneity of Prokaryotic Chromosomes. 3.1. Intrachromosomal Variance of Nucleotide and Oligonucleotide Composition3.2. Synonymous Codon Usage; 3.3. Identification of Genomic Islands and Lateral Gene Transfer Events; 3.4. G-C Skew; 4. Repeats in Prokaryotic Genomes; 4.1. Large Repeats and Duplications; 4.2. Transposons and Insertion Sequences; 4.3. Integrons; 4.4. Chimeric Mobile Elements: Conjugative Transposons, ICEs, Plasmid-Prophages, Transposon-Prophages, Genomic Islands, and Genetic Litter; 4.5. Retrons; 4.6. Short Dispersed Repeats; 4.7. Simple Sequence Repeats; 4.8. CRISPR Repeats; 5. Further Reading; Acknowledgments. 2. Genes in Prokaryotic Genomes and Their Computational Prediction Rajeev K. Azad1. Introduction; 2. Inhomogeneous Markov Models; 2.1. The GeneMark Program; 3. Interpolated Markov Models; 3.1. The Glimmer Program; 3.2. Using Deleted Interpolation in Gene Prediction; 4. Hidden Markov Models; 4.1. The Forward-Backward Algorithm; 4.2. The Viterbi Algorithm; 4.3. HMM Training; 4.4. The ECOPARSE Program; 4.5. The GeneHacker Program; 4.6. HMM Versions of the GeneMark Program; 5. Fourier Transform Methods; 5.1. The GeneScan Program; 5.2. The Lengthen-Shu.e Program; 6. Self-Organizing Maps. 6.1. The RescueNet Program7. Directed Acyclic Graphs; 7.1. The FrameD Program; 8. Linear Discriminant Function; 8.1. The ZCURVE Program; 9. Unsupervised Model Training: The Self-Learning Algorithms; 9.1. The GeneMark-Genesis Program; 9.2. The GeneMarkS Program; 9.3. The MED Program; 10. Using Similarity Search in Gene Prediction; 10.1. The ORPHEUS Program; 10.2. The CRITICA Program; 10.3. The BDGF Program; 10.4. The EasyGene Program; 10.5. The GISMO Program; 11. Gene Start Prediction; 12. Resolving Overlapping Genes; 13. Non-coding RNA Gene Prediction; 14. Assessing Gene Prediction Programs. 15. Discussion16. Further Reading; Acknowledgments; 3. Evolution of the Genetic Code: Computational Methods and Inferences Greg Fournier; 1. Introduction; 1.1. The Amino Acids; 1.2. Codon Designations; 1.3. Transfer RNA; 1.4. Aminoacyl-tRNA Synthetases; 2. Major Methods and Algorithms: Variations of the Genetic Code; 2.1. Non-canonical Codes; 2.2. Selenocysteine; 2.3. Pyrrolysine; 2.4. The Sep System; 2.5. Asparagine and Glutamine; 2.6. Evolutionary Considerations; 2.7. Nanoarchaeal tRNA; 3. Major Methods and Algorithms: Models of Genetic Code Evolution; 3.1. Overview. |
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Transfer RNA; 1.4. Aminoacyl-tRNA Synthetases; 2. Major Methods and Algorithms: Variations of the Genetic Code; 2.1. Non-canonical Codes; 2.2. Selenocysteine; 2.3. Pyrrolysine; 2.4. The Sep System; 2.5. Asparagine and Glutamine; 2.6. Evolutionary Considerations; 2.7. Nanoarchaeal tRNA; 3. Major Methods and Algorithms: Models of Genetic Code Evolution; 3.1. Overview.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Over 500 prokaryotic genomes have been sequenced to date, and thousands more have been planned for the next few years. While these genomic sequence data provide unprecedented opportunities for biologists to study the world of prokaryotes, they also raise extremely challenging issues such as how to decode the rich information encoded in these genomes. 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| genre | Textbooks fast |
| genre_facet | Textbooks |
| id | ZDB-4-EBA-ocn828425182 |
| illustrated | Illustrated |
| indexdate | 2024-11-27T13:25:11Z |
| institution | BVB |
| isbn | 9781860949838 1860949835 |
| issn | 1751-6404 ; |
| language | English |
| oclc_num | 828425182 |
| open_access_boolean | |
| owner | MAIN DE-863 DE-BY-FWS |
| owner_facet | MAIN DE-863 DE-BY-FWS |
| physical | 1 online resource (xix, 473 pages) : illustrations (some color) |
| psigel | ZDB-4-EBA |
| publishDate | 2008 |
| publishDateSearch | 2008 |
| publishDateSort | 2008 |
| publisher | Imperial College Press ; Distributed by World Scientific Publishing, |
| record_format | marc |
| series | Series on advances in bioinformatics and computational biology ; |
| series2 | Series on advances in bioinformatics and computational biology, |
| spelling | Computational methods for understanding bacterial and archaeal genomes / editors, Ying Xu, J. Peter Gogarten. London : Imperial College Press ; Hackensack, NJ : Distributed by World Scientific Publishing, ©2008. 1 online resource (xix, 473 pages) : illustrations (some color) text txt rdacontent computer c rdamedia online resource cr rdacarrier Series on advances in bioinformatics and computational biology, 1751-6404 ; v. 7 Includes bibliographical references (pages 397-466) and index. Print version record. Preface; CONTENTS; List of Contributors; Acknowledgments; 1. General Characteristics of Prokaryotic Genomes Jan Mr ́azek and Anne O. Summers; 1. Introduction; 1.1. The Replicon Concept and Classification of Replicons; 1.2. Physical Organization of Replicons in the Cell; 2. Overall Properties of Prokaryotic Chromosomes; 2.1. Size and Gene Content; 2.2. Why Are Prokaryotic Chromosomes Small?; 2.3. G+C Content; 2.4. Oligonucleotide Composition and Genome Signature; 2.5. Amino Acid Composition and Adaptation to Growth at High Temperatures; 3. Heterogeneity of Prokaryotic Chromosomes. 3.1. Intrachromosomal Variance of Nucleotide and Oligonucleotide Composition3.2. Synonymous Codon Usage; 3.3. Identification of Genomic Islands and Lateral Gene Transfer Events; 3.4. G-C Skew; 4. Repeats in Prokaryotic Genomes; 4.1. Large Repeats and Duplications; 4.2. Transposons and Insertion Sequences; 4.3. Integrons; 4.4. Chimeric Mobile Elements: Conjugative Transposons, ICEs, Plasmid-Prophages, Transposon-Prophages, Genomic Islands, and Genetic Litter; 4.5. Retrons; 4.6. Short Dispersed Repeats; 4.7. Simple Sequence Repeats; 4.8. CRISPR Repeats; 5. Further Reading; Acknowledgments. 2. Genes in Prokaryotic Genomes and Their Computational Prediction Rajeev K. Azad1. Introduction; 2. Inhomogeneous Markov Models; 2.1. The GeneMark Program; 3. Interpolated Markov Models; 3.1. The Glimmer Program; 3.2. Using Deleted Interpolation in Gene Prediction; 4. Hidden Markov Models; 4.1. The Forward-Backward Algorithm; 4.2. The Viterbi Algorithm; 4.3. HMM Training; 4.4. The ECOPARSE Program; 4.5. The GeneHacker Program; 4.6. HMM Versions of the GeneMark Program; 5. Fourier Transform Methods; 5.1. The GeneScan Program; 5.2. The Lengthen-Shu.e Program; 6. Self-Organizing Maps. 6.1. The RescueNet Program7. Directed Acyclic Graphs; 7.1. The FrameD Program; 8. Linear Discriminant Function; 8.1. The ZCURVE Program; 9. Unsupervised Model Training: The Self-Learning Algorithms; 9.1. The GeneMark-Genesis Program; 9.2. The GeneMarkS Program; 9.3. The MED Program; 10. Using Similarity Search in Gene Prediction; 10.1. The ORPHEUS Program; 10.2. The CRITICA Program; 10.3. The BDGF Program; 10.4. The EasyGene Program; 10.5. The GISMO Program; 11. Gene Start Prediction; 12. Resolving Overlapping Genes; 13. Non-coding RNA Gene Prediction; 14. Assessing Gene Prediction Programs. 15. Discussion16. Further Reading; Acknowledgments; 3. Evolution of the Genetic Code: Computational Methods and Inferences Greg Fournier; 1. Introduction; 1.1. The Amino Acids; 1.2. Codon Designations; 1.3. Transfer RNA; 1.4. Aminoacyl-tRNA Synthetases; 2. Major Methods and Algorithms: Variations of the Genetic Code; 2.1. Non-canonical Codes; 2.2. Selenocysteine; 2.3. Pyrrolysine; 2.4. The Sep System; 2.5. Asparagine and Glutamine; 2.6. Evolutionary Considerations; 2.7. Nanoarchaeal tRNA; 3. Major Methods and Algorithms: Models of Genetic Code Evolution; 3.1. Overview. Over 500 prokaryotic genomes have been sequenced to date, and thousands more have been planned for the next few years. While these genomic sequence data provide unprecedented opportunities for biologists to study the world of prokaryotes, they also raise extremely challenging issues such as how to decode the rich information encoded in these genomes. This comprehensive volume includes a collection of cohesively written chapters on prokaryotic genomes, their organization and evolution, the information they encode, and the computational approaches needed to derive such information. A comparative. Microbial genetics Data processing Textbooks. Bacterial genomes Data processing Textbooks. Prokaryotes Textbooks. Computational biology Textbooks. Bacterial genomes. http://id.loc.gov/authorities/subjects/sh2003008346 Microbial genetics. http://id.loc.gov/authorities/subjects/sh85084760 Genome, Bacterial Genome, Archaeal https://id.nlm.nih.gov/mesh/D020745 Genetics, Microbial Computational Biology methods Génomes bactériens. Génétique microbienne. SCIENCE Life Sciences Genetics & Genomics. bisacsh Microbial genetics fast Bacterial genomes fast Computational biology fast Prokaryotes fast Biochemistry. thema Computer science. thema Genetics (non-medical) thema Science. ukslc Textbooks fast Xu, Ying, 1960- https://id.oclc.org/worldcat/entity/E39PCjFYcHcxtgCf7GqKbwvd73 http://id.loc.gov/authorities/names/no2002057065 Gogarten, J. Peter. has work: Computational methods for understanding bacterial and archaeal genomes (Text) https://id.oclc.org/worldcat/entity/E39PCGFFfy6KTwmT3wJbTjgvQC https://id.oclc.org/worldcat/ontology/hasWork Print version: Computational methods for understanding bacterial and archaeal genomes. London : Imperial College Press ; Hackensack, NJ : Distributed by World Scientific Publishing, ©2008 1860949827 (DLC) 2008300872 (OCoLC)191658532 Series on advances in bioinformatics and computational biology ; v. 7. http://id.loc.gov/authorities/names/no2005039596 FWS01 ZDB-4-EBA FWS_PDA_EBA https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=516745 Volltext |
| spellingShingle | Computational methods for understanding bacterial and archaeal genomes / Series on advances in bioinformatics and computational biology ; Preface; CONTENTS; List of Contributors; Acknowledgments; 1. General Characteristics of Prokaryotic Genomes Jan Mr ́azek and Anne O. Summers; 1. Introduction; 1.1. The Replicon Concept and Classification of Replicons; 1.2. Physical Organization of Replicons in the Cell; 2. Overall Properties of Prokaryotic Chromosomes; 2.1. Size and Gene Content; 2.2. Why Are Prokaryotic Chromosomes Small?; 2.3. G+C Content; 2.4. Oligonucleotide Composition and Genome Signature; 2.5. Amino Acid Composition and Adaptation to Growth at High Temperatures; 3. Heterogeneity of Prokaryotic Chromosomes. 3.1. Intrachromosomal Variance of Nucleotide and Oligonucleotide Composition3.2. Synonymous Codon Usage; 3.3. Identification of Genomic Islands and Lateral Gene Transfer Events; 3.4. G-C Skew; 4. Repeats in Prokaryotic Genomes; 4.1. Large Repeats and Duplications; 4.2. Transposons and Insertion Sequences; 4.3. Integrons; 4.4. Chimeric Mobile Elements: Conjugative Transposons, ICEs, Plasmid-Prophages, Transposon-Prophages, Genomic Islands, and Genetic Litter; 4.5. Retrons; 4.6. Short Dispersed Repeats; 4.7. Simple Sequence Repeats; 4.8. CRISPR Repeats; 5. Further Reading; Acknowledgments. 2. Genes in Prokaryotic Genomes and Their Computational Prediction Rajeev K. Azad1. Introduction; 2. Inhomogeneous Markov Models; 2.1. The GeneMark Program; 3. Interpolated Markov Models; 3.1. The Glimmer Program; 3.2. Using Deleted Interpolation in Gene Prediction; 4. Hidden Markov Models; 4.1. The Forward-Backward Algorithm; 4.2. The Viterbi Algorithm; 4.3. HMM Training; 4.4. The ECOPARSE Program; 4.5. The GeneHacker Program; 4.6. HMM Versions of the GeneMark Program; 5. Fourier Transform Methods; 5.1. The GeneScan Program; 5.2. The Lengthen-Shu.e Program; 6. Self-Organizing Maps. 6.1. The RescueNet Program7. Directed Acyclic Graphs; 7.1. The FrameD Program; 8. Linear Discriminant Function; 8.1. The ZCURVE Program; 9. Unsupervised Model Training: The Self-Learning Algorithms; 9.1. The GeneMark-Genesis Program; 9.2. The GeneMarkS Program; 9.3. The MED Program; 10. Using Similarity Search in Gene Prediction; 10.1. The ORPHEUS Program; 10.2. The CRITICA Program; 10.3. The BDGF Program; 10.4. The EasyGene Program; 10.5. The GISMO Program; 11. Gene Start Prediction; 12. Resolving Overlapping Genes; 13. Non-coding RNA Gene Prediction; 14. Assessing Gene Prediction Programs. 15. Discussion16. Further Reading; Acknowledgments; 3. Evolution of the Genetic Code: Computational Methods and Inferences Greg Fournier; 1. Introduction; 1.1. The Amino Acids; 1.2. Codon Designations; 1.3. Transfer RNA; 1.4. Aminoacyl-tRNA Synthetases; 2. Major Methods and Algorithms: Variations of the Genetic Code; 2.1. Non-canonical Codes; 2.2. Selenocysteine; 2.3. Pyrrolysine; 2.4. The Sep System; 2.5. Asparagine and Glutamine; 2.6. Evolutionary Considerations; 2.7. Nanoarchaeal tRNA; 3. Major Methods and Algorithms: Models of Genetic Code Evolution; 3.1. Overview. Microbial genetics Data processing Textbooks. Bacterial genomes Data processing Textbooks. Prokaryotes Textbooks. Computational biology Textbooks. Bacterial genomes. http://id.loc.gov/authorities/subjects/sh2003008346 Microbial genetics. http://id.loc.gov/authorities/subjects/sh85084760 Genome, Bacterial Genome, Archaeal https://id.nlm.nih.gov/mesh/D020745 Genetics, Microbial Computational Biology methods Génomes bactériens. Génétique microbienne. SCIENCE Life Sciences Genetics & Genomics. bisacsh Microbial genetics fast Bacterial genomes fast Computational biology fast Prokaryotes fast Biochemistry. thema Computer science. thema Genetics (non-medical) thema Science. ukslc |
| subject_GND | http://id.loc.gov/authorities/subjects/sh2003008346 http://id.loc.gov/authorities/subjects/sh85084760 https://id.nlm.nih.gov/mesh/D020745 |
| title | Computational methods for understanding bacterial and archaeal genomes / |
| title_auth | Computational methods for understanding bacterial and archaeal genomes / |
| title_exact_search | Computational methods for understanding bacterial and archaeal genomes / |
| title_full | Computational methods for understanding bacterial and archaeal genomes / editors, Ying Xu, J. Peter Gogarten. |
| title_fullStr | Computational methods for understanding bacterial and archaeal genomes / editors, Ying Xu, J. Peter Gogarten. |
| title_full_unstemmed | Computational methods for understanding bacterial and archaeal genomes / editors, Ying Xu, J. Peter Gogarten. |
| title_short | Computational methods for understanding bacterial and archaeal genomes / |
| title_sort | computational methods for understanding bacterial and archaeal genomes |
| topic | Microbial genetics Data processing Textbooks. Bacterial genomes Data processing Textbooks. Prokaryotes Textbooks. Computational biology Textbooks. Bacterial genomes. http://id.loc.gov/authorities/subjects/sh2003008346 Microbial genetics. http://id.loc.gov/authorities/subjects/sh85084760 Genome, Bacterial Genome, Archaeal https://id.nlm.nih.gov/mesh/D020745 Genetics, Microbial Computational Biology methods Génomes bactériens. Génétique microbienne. SCIENCE Life Sciences Genetics & Genomics. bisacsh Microbial genetics fast Bacterial genomes fast Computational biology fast Prokaryotes fast Biochemistry. thema Computer science. thema Genetics (non-medical) thema Science. ukslc |
| topic_facet | Microbial genetics Data processing Textbooks. Bacterial genomes Data processing Textbooks. Prokaryotes Textbooks. Computational biology Textbooks. Bacterial genomes. Microbial genetics. Genome, Bacterial Genome, Archaeal Genetics, Microbial Computational Biology methods Génomes bactériens. Génétique microbienne. SCIENCE Life Sciences Genetics & Genomics. Microbial genetics Bacterial genomes Computational biology Prokaryotes Biochemistry. Computer science. Genetics (non-medical) Science. Textbooks |
| url | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=516745 |
| work_keys_str_mv | AT xuying computationalmethodsforunderstandingbacterialandarchaealgenomes AT gogartenjpeter computationalmethodsforunderstandingbacterialandarchaealgenomes |